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Examining More Lymph Nodes May Improve the Prognosis of Patients With Right Colon Cancer: Determining the Optimal Minimum Lymph Node Count

Authors :
Wentao Wu PhD
Daning Li MPH
Wen Ma PhD
Shuai Zheng MPH
Didi Han MPH
Fengshuo Xu MPH
Hong Yan PhD
Jun Lyu PhD
Source :
Cancer Control, Vol 28 (2021)
Publication Year :
2021
Publisher :
SAGE Publishing, 2021.

Abstract

Objectives The objective is to determine the optimal minimum lymph node examination number for right colon cancer (RCC) patients. Methods We comprehensively analysed the Surveillance, Epidemiology and End Results database data from 2004 to 2016 to determine the 13-year trend in the number of lymph nodes examined among 108,703 left colon cancer and 165,937 RCC patients. 133,137 RCC patients eligible for inclusion were used to determine the optimal minimum for lymph node examination. We used restricted cubic splines to analyse the dose-response relationship between the number of lymph nodes examined and prognosis. X-tiles and decision trees were used to determine the optimal cutoff for the number of lymph nodes based on the survival outcomes of patients with RCC. The Kaplan–Meier method and COX model were used to estimate the overall survival and independent prognostic factors, and a prediction model was constructed. The C-index, calibration curve, net reclassification improvement and integrated discrimination improvement were used to determine the predictive performance of the model, and decision curve analysis was used to evaluate the benefits. Results Lymph node examinations were common among colon cancer patients over the 13-year study period. It is generally agreed that at least 12 lymph nodes must be examined to ensure proper dissection and accurate staging of RCC; however, the optimal number of lymph nodes to be examined is controversial. The dose-response relationship indicated that 12 was not the optimal minimum number of lymph nodes for RCC patients. X-tile and survival decision-tree analysis indicated that 20 nodes was the optimal number. Survival analysis indicated that

Details

Language :
English
ISSN :
10732748
Volume :
28
Database :
Directory of Open Access Journals
Journal :
Cancer Control
Publication Type :
Academic Journal
Accession number :
edsdoj.7bbd6053d01b4d07bf8998e0f8daa53b
Document Type :
article
Full Text :
https://doi.org/10.1177/10732748211064034